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Row

State-wise Yield

Column

Foodgrains

Rice

Wheat

Coarse Cereals

Column

Foodgrains

Rice

Wheat

Coarse Cereals

Inferences - So here Inferences will come

Inferences - So here Inferences will come

Production

Row

Foodgrains

Rice

Wheat

Coarse Cereals

Comparison of Commodities

Row

Maize

Cereals

Tea

Coffee

Fruits

Rice

Wheat

Land Distribution

Column

Data According to Years by Waffle Chart

1990-91

2000-01

2009-10

2010-11

2011-12

                            Forest                      Net Area Sown 
                             71.60                             140.98 
 Other Uncultivated land excluding                        Fallow land 
                             26.11                              25.18 
Area not available for cultivation 
                             43.53 

function (parts, rows = 10, keep = TRUE, xlab = NULL, title = NULL, 
    colors = NA, size = 2, flip = FALSE, reverse = FALSE, equal = TRUE, 
    pad = 0, use_glyph = FALSE, glyph_size = 12, legend_pos = "right") 
{
    part_names <- names(parts)
    if (length(part_names) < length(parts)) {
        part_names <- c(part_names, LETTERS[1:length(parts) - 
            length(part_names)])
    }
    names(parts) <- part_names
    if (all(is.na(colors))) 
        colors <- suppressWarnings(brewer.pal(length(parts), 
            "Set2"))
    parts_vec <- unlist(sapply(1:length(parts), function(i) {
        rep(names(parts)[i], parts[i])
    }))
    if (reverse) 
        parts_vec <- rev(parts_vec)
    dat <- expand.grid(y = 1:rows, x = seq_len(pad + (ceiling(sum(parts)/rows))))
    dat$value <- c(parts_vec, rep(NA, nrow(dat) - length(parts_vec)))
    if (!inherits(use_glyph, "logical")) {
        fontlab <- rep(fa_unicode[use_glyph], length(unique(parts_vec)))
        dat$fontlab <- c(fontlab[as.numeric(factor(parts_vec))], 
            rep(NA, nrow(dat) - length(parts_vec)))
    }
    dat$value <- ifelse(is.na(dat$value), " ", dat$value)
    if (" " %in% dat$value) 
        part_names <- c(part_names, " ")
    if (" " %in% dat$value) 
        colors <- c(colors, "#00000000")
    dat$value <- factor(dat$value, levels = part_names)
    gg <- ggplot(dat, aes(x = x, y = y))
    if (flip) 
        gg <- ggplot(dat, aes(x = y, y = x))
    gg <- gg + theme_bw()
    if (inherits(use_glyph, "logical")) {
        gg <- gg + geom_tile(aes(fill = value), color = "white", 
            size = size)
        gg <- gg + scale_fill_manual(name = "", values = colors, 
            label = part_names, na.value = "white", drop = !keep)
        gg <- gg + guides(fill = guide_legend(override.aes = list(colour = "#00000000")))
        gg <- gg + theme(legend.background = element_rect(fill = "#00000000", 
            color = "#00000000"))
        gg <- gg + theme(legend.key = element_rect(fill = "#00000000", 
            color = "#00000000"))
    }
    else {
        if (choose_font("FontAwesome", quiet = TRUE) == "") {
            stop("FontAwesome not found. Install via: https://github.com/FortAwesome/Font-Awesome/tree/master/fonts", 
                call. = FALSE)
        }
        suppressWarnings(suppressMessages(font_import(system.file("fonts", 
            package = "waffle"), recursive = FALSE, prompt = FALSE)))
        if (!(!interactive() || stats::runif(1) > 0.1)) {
            message("Font Awesome by Dave Gandy - http://fontawesome.io")
        }
        gg <- gg + geom_tile(color = "#00000000", fill = "#00000000", 
            size = size, alpha = 0, show.legend = FALSE)
        gg <- gg + geom_point(aes(color = value), fill = "#00000000", 
            size = 0, show.legend = TRUE)
        gg <- gg + geom_text(aes(color = value, label = fontlab), 
            family = "FontAwesome", size = glyph_size, show.legend = FALSE)
        gg <- gg + scale_color_manual(name = "", values = colors, 
            labels = part_names, drop = !keep)
        gg <- gg + guides(color = guide_legend(override.aes = list(shape = 15, 
            size = 7)))
        gg <- gg + theme(legend.background = element_rect(fill = "#00000000", 
            color = "#00000000"))
        gg <- gg + theme(legend.key = element_rect(color = "#00000000"))
    }
    gg <- gg + labs(x = xlab, y = NULL, title = title)
    gg <- gg + scale_x_continuous(expand = c(0, 0))
    gg <- gg + scale_y_continuous(expand = c(0, 0))
    if (equal) 
        gg <- gg + coord_equal()
    gg <- gg + theme(panel.grid = element_blank())
    gg <- gg + theme(panel.border = element_blank())
    gg <- gg + theme(panel.background = element_blank())
    gg <- gg + theme(panel.spacing = unit(0, "null"))
    gg <- gg + theme(axis.text = element_blank())
    gg <- gg + theme(axis.title.x = element_text(size = 10))
    gg <- gg + theme(axis.ticks = element_blank())
    gg <- gg + theme(axis.line = element_blank())
    gg <- gg + theme(axis.ticks.length = unit(0, "null"))
    gg <- gg + theme(plot.title = element_text(size = 18))
    gg <- gg + theme(plot.background = element_blank())
    gg <- gg + theme(panel.spacing = unit(c(0, 0, 0, 0), "null"))
    gg <- gg + theme(legend.position = legend_pos)
    gg
}
<bytecode: 0x000000002a96f228>
<environment: namespace:waffle>

2012-13

2013-14

2014-15

2015-16

Column

Data According to Years by Pie Chart

1990-91

2000-01

2009-10

2010-11

2011-12

2012-13

2013-14

2014-15

2015-16

Productivity Scale

Land Usage using Line Graph

Total Exchg.

Column

Value of Imports vs Exports

Percentage share of Imports and Exports

Supply Estimates of Major Crops

Commodity Exc.

Column

Commodity Import

Commodity Export

Column

Import

Export

Regression

Column

Regression About Import

Regression About Export

Conclusion

Column

Inference about Crop Yield and Production

Column

Inference about Land Usage for Agriculture

Column

Inference about Imports & Exports of Agriculture Commodities